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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhongwen Li Haixin Huang Chuanzhi Zang Yu Haibin |
| Copyright Year | 2013 |
| Description | Author affiliation: Key Lab. of Networked Control Syst., Shenyang Inst. of Autom., Shenyang, China (Zhongwen Li; Haixin Huang; Chuanzhi Zang; Yu Haibin) |
| Abstract | The curtailment of the peak demand has great economic and environmental benefits. In this paper, an efficient price profile under the Real-Time Pricing (RTP) option is found out to optimize the regional domestic daily electric load curve. The domestic electric appliances are divided into eight categories, with respect to the difference of their self-price elasticity and cross-price elasticity. In order to set up a reasonable pricing strategy model, both the users' satisfaction and the price are taken into account. The program of RTP is taken and the Particle Swarm Optimization (PSO) algorithm is used to optimize the electricity price profile. Under the optimized price profile, the load curve tends to be more flat and the average price for the customer is lower than before, after the variation and shift of the electric power demand. |
| Sponsorship | IEEE Beijing Sect. |
| Starting Page | 449 |
| Ending Page | 455 |
| File Size | 387481 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781479900770 |
| DOI | 10.1109/ICCT.2013.6820418 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Elasticity Home appliances Load modeling Aggregates Mathematical model Pricing Optimization demand side management demand response real-time price particle swarm optimization electricity pricing strategy |
| Content Type | Text |
| Resource Type | Article |
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